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Product recommendation with latent review topics

Author

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  • Juheng Zhang

    (University of Massachusetts)

  • Selwyn Piramuthu

    (University of Florida)

Abstract

Online customer reviews complement information from product and service providers. While the latter is directly from the source of the product and/or service, the former is generally from users of these products and/or services. Clearly, these two information sets are generated from different perspectives with possibly different sets of intentions. For a prospective customer, both these perspectives together provide a complementary set of information and support their purchase decisions. Given the different perspective and incentive structure, the information from these two source sets tends to be necessarily biased, clearly with the high probability of negative information omission from that provided by the product/service providers. Moreover, customers oftentimes face information overload during their attempts at deciphering existing online customer reviews. We attempt to alleviate this through mining hidden information in online customer reviews. We use a variant of the Latent Dirichlet Allocation (LDA) model and clustering to generate equivalent options that the customer could then use in their purchase decisions. We illustrate this using online hotel review data.

Suggested Citation

  • Juheng Zhang & Selwyn Piramuthu, 2018. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 20(3), pages 617-625, June.
    • Handle: RePEc:spr:infosf:v:20:y:2018:i:3:d:10.1007_s10796-016-9697-z
    DOI: 10.1007/s10796-016-9697-z
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    References listed on IDEAS

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    1. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    2. Baron David P., 2002. "Private Ordering on the Internet: The EBay Community of Traders," Business and Politics, De Gruyter, vol. 4(3), pages 1-31, November.
    3. Hirshleifer, David & Teoh, Siew Hong, 2003. "Limited attention, information disclosure, and financial reporting," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 337-386, December.
    4. Stephen Burgess & Carmine Sellitto & Carmen Cox & Jeremy Buultjens, 2011. "Trust perceptions of online travel information by different content creators: Some social and legal implications," Information Systems Frontiers, Springer, vol. 13(2), pages 221-235, April.
    5. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    6. Healy, Paul M. & Palepu, Krishna G., 2001. "Information asymmetry, corporate disclosure, and the capital markets: A review of the empirical disclosure literature," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 405-440, September.
    7. Juheng Zhang & Haldun Aytug & Gary J. Koehler, 2014. "Research Note —Discriminant Analysis with Strategically Manipulated Data," Information Systems Research, INFORMS, vol. 25(3), pages 654-662, September.
    8. Xiangbin Yan & Jing Wang & Michael Chau, 2015. "Customer revisit intention to restaurants: Evidence from online reviews," Information Systems Frontiers, Springer, vol. 17(3), pages 645-657, June.
    9. Piramuthu, Selwyn, 2004. "Evaluating feature selection methods for learning in data mining applications," European Journal of Operational Research, Elsevier, vol. 156(2), pages 483-494, July.
    10. Zhang, Juheng & Aytug, Haldun, 2016. "Comparison of imputation methods for discriminant analysis with strategically hidden data," European Journal of Operational Research, Elsevier, vol. 255(2), pages 522-530.
    11. Selwyn Piramuthu, 1999. "Feature Selection for Financial Credit-Risk Evaluation Decisions," INFORMS Journal on Computing, INFORMS, vol. 11(3), pages 258-266, August.
    12. Sparks, Beverley A. & Browning, Victoria, 2011. "The impact of online reviews on hotel booking intentions and perception of trust," Tourism Management, Elsevier, vol. 32(6), pages 1310-1323.
    13. Baron, David P., 2002. "Private Ordering on the Internet: The eBay Community of Traders," Business and Politics, Cambridge University Press, vol. 4(3), pages 245-274, November.
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    Cited by:

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    2. Hung-Pin Shih & Pei-Chen Sung, 2021. "Addressing the Review-Based Learning and Private Information Approaches to Foster Platform Continuance," Information Systems Frontiers, Springer, vol. 23(3), pages 649-661, June.
    3. Shalak Mendon & Pankaj Dutta & Abhishek Behl & Stefan Lessmann, 2021. "A Hybrid Approach of Machine Learning and Lexicons to Sentiment Analysis: Enhanced Insights from Twitter Data of Natural Disasters," Information Systems Frontiers, Springer, vol. 23(5), pages 1145-1168, September.
    4. Peng Xie, 2022. "The Interplay Between Investor Activity on Virtual Investment Community and the Trading Dynamics: Evidence From the Bitcoin Market," Information Systems Frontiers, Springer, vol. 24(4), pages 1287-1303, August.
    5. Weiwei Deng, 2022. "Leveraging consumer behaviors for product recommendation: an approach based on heterogeneous network," Electronic Commerce Research, Springer, vol. 22(4), pages 1079-1105, December.
    6. Luvai Motiwalla & Amit V. Deokar & Surendra Sarnikar & Angelika Dimoka, 2019. "Leveraging Data Analytics for Behavioral Research," Information Systems Frontiers, Springer, vol. 21(4), pages 735-742, August.
    7. Ali M Ahmed Al-Sabaawi & Hacer Karacan & Yusuf Erkan Yenice, 2020. "Exploiting implicit social relationships via dimension reduction to improve recommendation system performance," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-18, April.

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